Identifying an odour source in fluid-advected environments, algorithms abstracted from moth-inspired plume tracing strategies

Abstract

This paper presents algorithms for identifying the odour source of a chemical plume with significant filament intermittency and meander developed in fluid-advected environments. The algorithms are abstracted from moth-inspired chemical plume tracing strategies in two steps. First, we introduce the concept of the last chemical detection points that leads to construction of a source identification zone and development of two variations in the source identification algorithms. Second, we use Monte Carlo methods to optimise the proposed algorithms in a simulated environment. The evaluation results demonstrate that the optimised algorithm achieves a success rate of over 90% in identifying the source location, the average identification time is 3–4 min and the average error is 1–2 m surrounding the source location.

Keywords:

• biologically inspired searching strategy
• chemical plume tracing
• odour source localization
• olfaction-based navigation

Acknowledgment

Jay Farrell, Ring Cardé and John Murlis provided valuable insight into the processes of moth-inspired plume tracing strategies. The author thanks his students with the Department of Computer Science at California State University, Bakersfield, for their efforts in performing simulation test runs.